Wireless communication systems are widely deployed to provide, for example, a broad range of voice and data-related services. Typical wireless communication systems consist of multiple-access communication networks that allow users to share common network resources. Examples of these networks are time division multiple access (“TDMA”) systems, code division multiple access (“CDMA”) systems, single-carrier frequency division multiple access (“SC-FDMA”) systems, orthogonal frequency division multiple access (“OFDMA”) systems, or other like systems. An OFDMA system is adopted by various technology standards such as evolved universal terrestrial radio access (“E-UTRA”), Wi-Fi, worldwide interoperability for microwave access (“WiMAX”), ultra mobile broadband (“UMB”), and other similar systems. Further, the implementations of these systems are described by specifications developed by various standards bodies such as the third generation partnership project (“3GPP”) and 3GPP2.
As wireless communication systems evolve, more advanced network equipment is introduced that provide improved features, functionality, and performance. A representation of such advanced network equipment may also be referred to as long-term evolution (“LTE”) equipment or long-term evolution advanced (“LTE-A”) equipment. LTE is the next step in the evolution of high-speed packet access (“HSPA”) with higher average and peak data throughput rates, lower latency and a better user experience especially in high-demand geographic areas. LTE accomplishes this higher performance with the use of broader spectrum bandwidth, OFDMA and SC-FDMA air interfaces, and advanced antenna methods.
Communications between wireless devices and base stations may be established using single-input, single-output (“SISO”) mode, where only one antenna is used for both the receiver and transmitter; single-input, multiple-output (“SIMO”) mode, where multiple antennas may be used at the receiver and only one antenna is used at the transmitter; multiple-input, single-output (“MISO”) mode, where multiple antennas may be used at the transmitter and only one antenna is used at the receiver; and multiple-input, multiple-output (“MIMO”) mode, where multiple antennas may be used at the receiver and transmitter. Compared to SISO mode, SIMO mode may provide increased coverage while MIMO mode may provide increased coverage and spectral efficiency and higher data throughput if the multiple transmit antennas, multiple receive antennas or both are utilized. When wireless devices using MIMO mode are employed additional MIMO operating modes are available. These operating modes include diversity MIMO mode, single-user MIMO mode, multiple-user MIMO mode and mixed MIMO mode. Diversity MIMO-mode uses multiple transmit and receive antennas to take advantage of the spatial dimensionality of the wireless communication radio frequency (“RF”) channel to provide more reliable transmission of a single data channel. It is important to recognize that systems employing base stations using MIMO mode can typically support wireless devices operating in SISO mode, SIMO mode, MISO mode, MIMO mode, other operating modes or combinations of operating modes.
Single-user MIMO (“SU-MIMO”) mode takes advantage of the spatial dimensionality of the wireless communication RF channel by using multiple transmit and receive antennas to provide multiple concurrent transmission data channels for increased data rates of a single wireless device. Similarly, multiple-user MIMO (“MU-MIMO”) mode uses multiple transmit and receive antennas to provide multiple concurrent transmission data channels to multiple wireless devices. Mixed MIMO mode concurrently supports the combination of SIMO and MIMO wireless devices on the same RF channel. Uplink (“UL”) communication refers to communication from a wireless device to a base station. Downlink (“DL”) communication refers to communication from a base station to a wireless device.
As specified in 3rd Generation Partnership Project; Technical Specification Group Radio Access Network; Physical Channels and Modulation (Release 8), 3GPP, 3GPP TS 36 series of specifications (“LTE Release 8”), the use of multiple antenna techniques is supported for DL transmission. In 3rd Generation Partnership Project; Technical Specification Group Radio Access Network; Further Advancements For E-UTRA; Physical Layer Aspects (Release 9), 3GPP, 3GPP TR 36.814 V1.1.1 (2009-06) (“LTE-A Release 10”), multiple antenna techniques may be used to improve DL performance. Such multiple antenna techniques include, for instance, transmit diversity and spatial multiplexing. Various transmit diversity schemes may be used such as space frequency block coding (“SFBC”), space time block coding (“STBC”), frequency switched transmit diversity (“FSTD”), time switched transmit diversity (“TSTD”), pre-coding vector switching (“PVS”), cyclic delay diversity (“CDD”), space code transmit diversity (“SCTD”), spatial orthogonal resource transmission diversity (“SORTD”), and other similar approaches. Some of these approaches have been adopted for use in LTE Release 8.
There has been extensive research on DL MU-MIMO transmission as can be found in the literature. One of the challenges in the implementation of DL MU-MIMO transmission is the effects of RF interference from signals transmitted to other wireless devices due to the lack of perfect channel state information (“CSI”) at the base station and wireless devices. This may degrade the performance of DL MU-MIMO transmission dramatically and may even question the benefit of using DL MU-MIMO transmission. In LTE Release 8, more emphasis was placed on wireless device-transparent schemes in which the wireless device's operation is similar between SU-MIMO mode and MU-MIMO mode than on improving the performance of MU-MIMO mode. In LTE-A Release 10, new schemes for MU-MIMO mode have been proposed to improve system performance. Many of these new schemes are more complex and require more feedback and signaling overhead from the wireless device to the base station as compared to LTE Release 8 MU-MIMO modes. Thus, there is a need to provide a lower-complexity DL MU-MIMO transmission with limited feedback overhead while still achieving improved system performance.
DL MU-MIMO mode can be modeled as a MIMO broadcast channel (“MIMO-BC”) in which a base station with multiple output antennas transmits multiple concurrent data channels to multiple wireless devices having multiple input antennas. Due to its simplicity, linear precoding has been considered a potential scheme for DL MU-MIMO mode. Linear precoding consists of linearly combining data channels to be transmitted to different wireless devices. This linear combination of data channels is performed to maximize the throughput of each wireless device. This requires the base station to have substantial knowledge of the channel state information (“CSI”) as observed by each wireless device. In practical applications, it is unrealistic to have substantial knowledge of the CSI especially for systems operating in frequency division duplexing (“FDD”) mode, which may require the wireless devices to feedback CSI to the base station. Thus, there is an additional need to provide solutions that require less knowledge of the channel state information at the transmitter (“CSIT”).
Another advantage of using DL MU-MIMO mode is the paradoxical increase in system capacity as the number of wireless devices increase, which is also known as multi-user diversity gain. This concept means that the system can increase throughput by scheduling each wireless device's transmission on its most favorable RF channels.
The CSI feedback schemes considered for implementation in LTE-A Release 10 can be divided into explicit feedback schemes and implicit feedback schemes. Explicit feedback schemes feedback a substantial representation of CSI in the form of, for instance, a covariance matrix, eigenvector, other forms or combination of forms from each wireless device to the base station. Explicit feedback schemes provide improved performance but require transmitting a significant amount of CSI values from each wireless device to the base station. Alternatively, implicit feedback schemes feedback reduced representation of CSI in the form of, for instance, channel indication information from each wireless device to the base station. For example, LTE Release 8 provides for a reduced representation of CSI in the form of a channel quality indication (“CQI”) data field, a precoding matrix index (“PMI”) data field and a rank indication (“RI”) data field.
While implicit feedback schemes provide less feedback information than explicit feedback schemes, implicit feedback schemes may have several disadvantages. The quantization error resulting from reduced representation of CSI may lead to increased interference from other wireless devices, which may degrade overall system performance. Further, the reduced representation of CSI may not contain enough channel information. This could inhibit the base station's ability to, for instance, suppress interference due to transmissions to other wireless devices, since in determining the reduced representation of CSI to be sent to the base station each wireless device may not know which other wireless devices it may be paired with by the base station.
One method to limit the resulting interference from other wireless devices is for each wireless device to also provide the base station with a best companion (“BC”) report, which reports a codeword set that may result in the least amount of interference from base station transmissions to other wireless devices in MU-MIMO mode. This method can significantly reduce the amount of interference from transmissions to other wireless devices at the cost of additional feedback overhead.
In DL MU-MIMO transmission, another method to address the problem associated with interference from base station transmissions to other wireless devices is for the base station to estimate a CQI. Such estimated CQI is based on projecting the CQI feedback from each wireless device, which are determined based on SU-MIMO mode. By estimating such CQI, the effects of interference from transmissions to other wireless devices will be taken into account, which can lead to more accurate coding and modulation assignments for each wireless device. However, these CQI values estimated at the base station may not be sufficiently accurate or consistent since the base station may not have perfect knowledge of the channel or the receiver algorithms used by each wireless device.